activity
20162026
most citedAya 23: Open Weight Releases to Further Multilingual Progress

9 citations · 14 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2026

CALIBER: Calibrating Confidence Before and After Reasoning in Language Models

Conor Finlay, Joshua Kurien, Saurabh Dash +2

Reasoning language models are increasingly asked not only to answer difficult questions, but also to estimate their likelihood of success. Existing methods typically elicit confide…

cs.CL2026

Soft-SVeRL: Self-Verified Reinforcement Learning with Soft Rewards

Saurabh Dash, Pierre Clavier, John Dang +4

Reinforcement Learning from Verifiable Rewards (RLVR) has improved language models in domains such as mathematics and code, where correctness can be checked automatically. However,…

cs.CL2026

Tiny Aya: Bridging Scale and Multilingual Depth

Alejandro R. Salamanca, Diana Abagyan, Daniel D'souza +23

Tiny Aya redefines what a small multilingual language model can achieve. Trained on 70 languages and refined through region-aware posttraining, it delivers state-of-the-art in tran…

cs.CL2025

Aya Vision: Advancing the Frontier of Multilingual Multimodality

Saurabh Dash, Yiyang Nan, John Dang +22

Building multimodal language models is fundamentally challenging: it requires aligning vision and language modalities, curating high-quality instruction data, and avoiding the degr…

cs.CL2025

Command A: An Enterprise-Ready Large Language Model

Team Cohere, :, Aakanksha +227

In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…

cs.CL2024★ 2 cited

How Does Quantization Affect Multilingual LLMs?

Kelly Marchisio, Saurabh Dash, Hongyu Chen +4

Quantization techniques are widely used to improve inference speed and deployment of large language models. While a wide body of work examines the impact of quantization on LLMs in…

cs.LG2024

Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs

Davide Paglieri, Saurabh Dash, Tim Rocktäschel +1

Post-Training Quantization (PTQ) enhances the efficiency of Large Language Models (LLMs) by enabling faster operation and compatibility with more accessible hardware through reduce…

cs.CL2024★ 9 cited

Aya 23: Open Weight Releases to Further Multilingual Progress

Viraat Aryabumi, John Dang, Dwarak Talupuru +18

This technical report introduces Aya 23, a family of multilingual language models. Aya 23 builds on the recent release of the Aya model (Üstün et al., 2024), focusing on pairing a…

cs.RO2016★ 3 cited

Low Cost Autonomous Navigation and Control of a Mechanically Balanced Bicycle with Dual Locomotion Mode

Ayush Pandey, Subhamoy Mahajan, Adarsh Kosta +17

On the lines of the huge and varied efforts in the field of automation with respect to technology development and innovation of vehicles to make them run autonomously, this paper p…